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<h1><a href="dialogflow_v3beta1.html">Dialogflow API</a> . <a href="dialogflow_v3beta1.projects.html">projects</a> . <a href="dialogflow_v3beta1.projects.locations.html">locations</a> . <a href="dialogflow_v3beta1.projects.locations.agents.html">agents</a> . <a href="dialogflow_v3beta1.projects.locations.agents.generators.html">generators</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
  <code><a href="#close">close()</a></code></p>
<p class="firstline">Close httplib2 connections.</p>
<p class="toc_element">
  <code><a href="#create">create(parent, body=None, languageCode=None, x__xgafv=None)</a></code></p>
<p class="firstline">Creates a generator in the specified agent.</p>
<p class="toc_element">
  <code><a href="#delete">delete(name, force=None, x__xgafv=None)</a></code></p>
<p class="firstline">Deletes the specified generators.</p>
<p class="toc_element">
  <code><a href="#get">get(name, languageCode=None, x__xgafv=None)</a></code></p>
<p class="firstline">Retrieves the specified generator.</p>
<p class="toc_element">
  <code><a href="#list">list(parent, languageCode=None, pageSize=None, pageToken=None, x__xgafv=None)</a></code></p>
<p class="firstline">Returns the list of all generators in the specified agent.</p>
<p class="toc_element">
  <code><a href="#list_next">list_next()</a></code></p>
<p class="firstline">Retrieves the next page of results.</p>
<p class="toc_element">
  <code><a href="#patch">patch(name, body=None, languageCode=None, updateMask=None, x__xgafv=None)</a></code></p>
<p class="firstline">Update the specified generator.</p>
<h3>Method Details</h3>
<div class="method">
    <code class="details" id="close">close()</code>
  <pre>Close httplib2 connections.</pre>
</div>

<div class="method">
    <code class="details" id="create">create(parent, body=None, languageCode=None, x__xgafv=None)</code>
  <pre>Creates a generator in the specified agent.

Args:
  parent: string, Required. The agent to create a generator for. Format: `projects//locations//agents/`. (required)
  body: object, The request body.
    The object takes the form of:

{ # Generators contain prompt to be sent to the LLM model to generate text. The prompt can contain parameters which will be resolved before calling the model. It can optionally contain banned phrases to ensure the model responses are safe.
  &quot;displayName&quot;: &quot;A String&quot;, # Required. The human-readable name of the generator, unique within the agent. The prompt contains pre-defined parameters such as $conversation, $last-user-utterance, etc. populated by Dialogflow. It can also contain custom placeholders which will be resolved during fulfillment.
  &quot;llmModelSettings&quot;: { # Settings for LLM models. # The LLM model settings.
    &quot;model&quot;: &quot;A String&quot;, # The selected LLM model.
    &quot;parameters&quot;: { # Generative model parameters to control the model behavior. # Generative model parameters.
      &quot;inputTokenLimit&quot;: &quot;A String&quot;, # The input token limit. This setting is currently only supported by playbooks.
      &quot;outputTokenLimit&quot;: &quot;A String&quot;, # The output token limit. This setting is currently only supported by playbooks. Only one of output_token_limit and max_output_tokens is allowed to be set.
      &quot;temperature&quot;: 3.14, # The temperature used for sampling during response generation. Value ranges from 0 to 1. Temperature controls the degree of randomness in token selection. Lower temperature means less randomness, while higher temperature means more randomness. Valid range: [0.0, 1.0]
    },
    &quot;promptText&quot;: &quot;A String&quot;, # The custom prompt to use.
  },
  &quot;modelParameter&quot;: { # Parameters to be passed to the LLM. If not set, default values will be used. # Parameters passed to the LLM to configure its behavior.
    &quot;maxDecodeSteps&quot;: 42, # The maximum number of tokens to generate.
    &quot;temperature&quot;: 3.14, # The temperature used for sampling. Temperature sampling occurs after both topP and topK have been applied. Valid range: [0.0, 1.0] Low temperature = less random. High temperature = more random.
    &quot;topK&quot;: 42, # If set, the sampling process in each step is limited to the top_k tokens with highest probabilities. Valid range: [1, 40] or 1000+. Small topK = less random. Large topK = more random.
    &quot;topP&quot;: 3.14, # If set, only the tokens comprising the top top_p probability mass are considered. If both top_p and top_k are set, top_p will be used for further refining candidates selected with top_k. Valid range: (0.0, 1.0]. Small topP = less random. Large topP = more random.
  },
  &quot;name&quot;: &quot;A String&quot;, # The unique identifier of the generator. Must be set for the Generators.UpdateGenerator method. Generators.CreateGenerate populates the name automatically. Format: `projects//locations//agents//generators/`.
  &quot;placeholders&quot;: [ # Optional. List of custom placeholders in the prompt text.
    { # Represents a custom placeholder in the prompt text.
      &quot;id&quot;: &quot;A String&quot;, # Unique ID used to map custom placeholder to parameters in fulfillment.
      &quot;name&quot;: &quot;A String&quot;, # Custom placeholder value in the prompt text.
    },
  ],
  &quot;promptText&quot;: { # Text input which can be used for prompt or banned phrases. # Required. Prompt for the LLM model.
    &quot;text&quot;: &quot;A String&quot;, # Required. Text input which can be used for prompt or banned phrases.
  },
}

  languageCode: string, The language to create generators for the following fields: * `Generator.prompt_text.text` If not specified, the agent&#x27;s default language is used.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Generators contain prompt to be sent to the LLM model to generate text. The prompt can contain parameters which will be resolved before calling the model. It can optionally contain banned phrases to ensure the model responses are safe.
  &quot;displayName&quot;: &quot;A String&quot;, # Required. The human-readable name of the generator, unique within the agent. The prompt contains pre-defined parameters such as $conversation, $last-user-utterance, etc. populated by Dialogflow. It can also contain custom placeholders which will be resolved during fulfillment.
  &quot;llmModelSettings&quot;: { # Settings for LLM models. # The LLM model settings.
    &quot;model&quot;: &quot;A String&quot;, # The selected LLM model.
    &quot;parameters&quot;: { # Generative model parameters to control the model behavior. # Generative model parameters.
      &quot;inputTokenLimit&quot;: &quot;A String&quot;, # The input token limit. This setting is currently only supported by playbooks.
      &quot;outputTokenLimit&quot;: &quot;A String&quot;, # The output token limit. This setting is currently only supported by playbooks. Only one of output_token_limit and max_output_tokens is allowed to be set.
      &quot;temperature&quot;: 3.14, # The temperature used for sampling during response generation. Value ranges from 0 to 1. Temperature controls the degree of randomness in token selection. Lower temperature means less randomness, while higher temperature means more randomness. Valid range: [0.0, 1.0]
    },
    &quot;promptText&quot;: &quot;A String&quot;, # The custom prompt to use.
  },
  &quot;modelParameter&quot;: { # Parameters to be passed to the LLM. If not set, default values will be used. # Parameters passed to the LLM to configure its behavior.
    &quot;maxDecodeSteps&quot;: 42, # The maximum number of tokens to generate.
    &quot;temperature&quot;: 3.14, # The temperature used for sampling. Temperature sampling occurs after both topP and topK have been applied. Valid range: [0.0, 1.0] Low temperature = less random. High temperature = more random.
    &quot;topK&quot;: 42, # If set, the sampling process in each step is limited to the top_k tokens with highest probabilities. Valid range: [1, 40] or 1000+. Small topK = less random. Large topK = more random.
    &quot;topP&quot;: 3.14, # If set, only the tokens comprising the top top_p probability mass are considered. If both top_p and top_k are set, top_p will be used for further refining candidates selected with top_k. Valid range: (0.0, 1.0]. Small topP = less random. Large topP = more random.
  },
  &quot;name&quot;: &quot;A String&quot;, # The unique identifier of the generator. Must be set for the Generators.UpdateGenerator method. Generators.CreateGenerate populates the name automatically. Format: `projects//locations//agents//generators/`.
  &quot;placeholders&quot;: [ # Optional. List of custom placeholders in the prompt text.
    { # Represents a custom placeholder in the prompt text.
      &quot;id&quot;: &quot;A String&quot;, # Unique ID used to map custom placeholder to parameters in fulfillment.
      &quot;name&quot;: &quot;A String&quot;, # Custom placeholder value in the prompt text.
    },
  ],
  &quot;promptText&quot;: { # Text input which can be used for prompt or banned phrases. # Required. Prompt for the LLM model.
    &quot;text&quot;: &quot;A String&quot;, # Required. Text input which can be used for prompt or banned phrases.
  },
}</pre>
</div>

<div class="method">
    <code class="details" id="delete">delete(name, force=None, x__xgafv=None)</code>
  <pre>Deletes the specified generators.

Args:
  name: string, Required. The name of the generator to delete. Format: `projects//locations//agents//generators/`. (required)
  force: boolean, This field has no effect for generators not being used. For generators that are used by pages/flows/transition route groups: * If `force` is set to false, an error will be returned with message indicating the referenced resources. * If `force` is set to true, Dialogflow will remove the generator, as well as any references to the generator (i.e. Generator) in fulfillments.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
}</pre>
</div>

<div class="method">
    <code class="details" id="get">get(name, languageCode=None, x__xgafv=None)</code>
  <pre>Retrieves the specified generator.

Args:
  name: string, Required. The name of the generator. Format: `projects//locations//agents//generators/`. (required)
  languageCode: string, The language to list generators for.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Generators contain prompt to be sent to the LLM model to generate text. The prompt can contain parameters which will be resolved before calling the model. It can optionally contain banned phrases to ensure the model responses are safe.
  &quot;displayName&quot;: &quot;A String&quot;, # Required. The human-readable name of the generator, unique within the agent. The prompt contains pre-defined parameters such as $conversation, $last-user-utterance, etc. populated by Dialogflow. It can also contain custom placeholders which will be resolved during fulfillment.
  &quot;llmModelSettings&quot;: { # Settings for LLM models. # The LLM model settings.
    &quot;model&quot;: &quot;A String&quot;, # The selected LLM model.
    &quot;parameters&quot;: { # Generative model parameters to control the model behavior. # Generative model parameters.
      &quot;inputTokenLimit&quot;: &quot;A String&quot;, # The input token limit. This setting is currently only supported by playbooks.
      &quot;outputTokenLimit&quot;: &quot;A String&quot;, # The output token limit. This setting is currently only supported by playbooks. Only one of output_token_limit and max_output_tokens is allowed to be set.
      &quot;temperature&quot;: 3.14, # The temperature used for sampling during response generation. Value ranges from 0 to 1. Temperature controls the degree of randomness in token selection. Lower temperature means less randomness, while higher temperature means more randomness. Valid range: [0.0, 1.0]
    },
    &quot;promptText&quot;: &quot;A String&quot;, # The custom prompt to use.
  },
  &quot;modelParameter&quot;: { # Parameters to be passed to the LLM. If not set, default values will be used. # Parameters passed to the LLM to configure its behavior.
    &quot;maxDecodeSteps&quot;: 42, # The maximum number of tokens to generate.
    &quot;temperature&quot;: 3.14, # The temperature used for sampling. Temperature sampling occurs after both topP and topK have been applied. Valid range: [0.0, 1.0] Low temperature = less random. High temperature = more random.
    &quot;topK&quot;: 42, # If set, the sampling process in each step is limited to the top_k tokens with highest probabilities. Valid range: [1, 40] or 1000+. Small topK = less random. Large topK = more random.
    &quot;topP&quot;: 3.14, # If set, only the tokens comprising the top top_p probability mass are considered. If both top_p and top_k are set, top_p will be used for further refining candidates selected with top_k. Valid range: (0.0, 1.0]. Small topP = less random. Large topP = more random.
  },
  &quot;name&quot;: &quot;A String&quot;, # The unique identifier of the generator. Must be set for the Generators.UpdateGenerator method. Generators.CreateGenerate populates the name automatically. Format: `projects//locations//agents//generators/`.
  &quot;placeholders&quot;: [ # Optional. List of custom placeholders in the prompt text.
    { # Represents a custom placeholder in the prompt text.
      &quot;id&quot;: &quot;A String&quot;, # Unique ID used to map custom placeholder to parameters in fulfillment.
      &quot;name&quot;: &quot;A String&quot;, # Custom placeholder value in the prompt text.
    },
  ],
  &quot;promptText&quot;: { # Text input which can be used for prompt or banned phrases. # Required. Prompt for the LLM model.
    &quot;text&quot;: &quot;A String&quot;, # Required. Text input which can be used for prompt or banned phrases.
  },
}</pre>
</div>

<div class="method">
    <code class="details" id="list">list(parent, languageCode=None, pageSize=None, pageToken=None, x__xgafv=None)</code>
  <pre>Returns the list of all generators in the specified agent.

Args:
  parent: string, Required. The agent to list all generators for. Format: `projects//locations//agents/`. (required)
  languageCode: string, The language to list generators for.
  pageSize: integer, The maximum number of items to return in a single page. By default 100 and at most 1000.
  pageToken: string, The next_page_token value returned from a previous list request.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # The response message for Generators.ListGenerators.
  &quot;generators&quot;: [ # The list of generators. There will be a maximum number of items returned based on the page_size field in the request.
    { # Generators contain prompt to be sent to the LLM model to generate text. The prompt can contain parameters which will be resolved before calling the model. It can optionally contain banned phrases to ensure the model responses are safe.
      &quot;displayName&quot;: &quot;A String&quot;, # Required. The human-readable name of the generator, unique within the agent. The prompt contains pre-defined parameters such as $conversation, $last-user-utterance, etc. populated by Dialogflow. It can also contain custom placeholders which will be resolved during fulfillment.
      &quot;llmModelSettings&quot;: { # Settings for LLM models. # The LLM model settings.
        &quot;model&quot;: &quot;A String&quot;, # The selected LLM model.
        &quot;parameters&quot;: { # Generative model parameters to control the model behavior. # Generative model parameters.
          &quot;inputTokenLimit&quot;: &quot;A String&quot;, # The input token limit. This setting is currently only supported by playbooks.
          &quot;outputTokenLimit&quot;: &quot;A String&quot;, # The output token limit. This setting is currently only supported by playbooks. Only one of output_token_limit and max_output_tokens is allowed to be set.
          &quot;temperature&quot;: 3.14, # The temperature used for sampling during response generation. Value ranges from 0 to 1. Temperature controls the degree of randomness in token selection. Lower temperature means less randomness, while higher temperature means more randomness. Valid range: [0.0, 1.0]
        },
        &quot;promptText&quot;: &quot;A String&quot;, # The custom prompt to use.
      },
      &quot;modelParameter&quot;: { # Parameters to be passed to the LLM. If not set, default values will be used. # Parameters passed to the LLM to configure its behavior.
        &quot;maxDecodeSteps&quot;: 42, # The maximum number of tokens to generate.
        &quot;temperature&quot;: 3.14, # The temperature used for sampling. Temperature sampling occurs after both topP and topK have been applied. Valid range: [0.0, 1.0] Low temperature = less random. High temperature = more random.
        &quot;topK&quot;: 42, # If set, the sampling process in each step is limited to the top_k tokens with highest probabilities. Valid range: [1, 40] or 1000+. Small topK = less random. Large topK = more random.
        &quot;topP&quot;: 3.14, # If set, only the tokens comprising the top top_p probability mass are considered. If both top_p and top_k are set, top_p will be used for further refining candidates selected with top_k. Valid range: (0.0, 1.0]. Small topP = less random. Large topP = more random.
      },
      &quot;name&quot;: &quot;A String&quot;, # The unique identifier of the generator. Must be set for the Generators.UpdateGenerator method. Generators.CreateGenerate populates the name automatically. Format: `projects//locations//agents//generators/`.
      &quot;placeholders&quot;: [ # Optional. List of custom placeholders in the prompt text.
        { # Represents a custom placeholder in the prompt text.
          &quot;id&quot;: &quot;A String&quot;, # Unique ID used to map custom placeholder to parameters in fulfillment.
          &quot;name&quot;: &quot;A String&quot;, # Custom placeholder value in the prompt text.
        },
      ],
      &quot;promptText&quot;: { # Text input which can be used for prompt or banned phrases. # Required. Prompt for the LLM model.
        &quot;text&quot;: &quot;A String&quot;, # Required. Text input which can be used for prompt or banned phrases.
      },
    },
  ],
  &quot;nextPageToken&quot;: &quot;A String&quot;, # Token to retrieve the next page of results, or empty if there are no more results in the list.
}</pre>
</div>

<div class="method">
    <code class="details" id="list_next">list_next()</code>
  <pre>Retrieves the next page of results.

        Args:
          previous_request: The request for the previous page. (required)
          previous_response: The response from the request for the previous page. (required)

        Returns:
          A request object that you can call &#x27;execute()&#x27; on to request the next
          page. Returns None if there are no more items in the collection.
        </pre>
</div>

<div class="method">
    <code class="details" id="patch">patch(name, body=None, languageCode=None, updateMask=None, x__xgafv=None)</code>
  <pre>Update the specified generator.

Args:
  name: string, The unique identifier of the generator. Must be set for the Generators.UpdateGenerator method. Generators.CreateGenerate populates the name automatically. Format: `projects//locations//agents//generators/`. (required)
  body: object, The request body.
    The object takes the form of:

{ # Generators contain prompt to be sent to the LLM model to generate text. The prompt can contain parameters which will be resolved before calling the model. It can optionally contain banned phrases to ensure the model responses are safe.
  &quot;displayName&quot;: &quot;A String&quot;, # Required. The human-readable name of the generator, unique within the agent. The prompt contains pre-defined parameters such as $conversation, $last-user-utterance, etc. populated by Dialogflow. It can also contain custom placeholders which will be resolved during fulfillment.
  &quot;llmModelSettings&quot;: { # Settings for LLM models. # The LLM model settings.
    &quot;model&quot;: &quot;A String&quot;, # The selected LLM model.
    &quot;parameters&quot;: { # Generative model parameters to control the model behavior. # Generative model parameters.
      &quot;inputTokenLimit&quot;: &quot;A String&quot;, # The input token limit. This setting is currently only supported by playbooks.
      &quot;outputTokenLimit&quot;: &quot;A String&quot;, # The output token limit. This setting is currently only supported by playbooks. Only one of output_token_limit and max_output_tokens is allowed to be set.
      &quot;temperature&quot;: 3.14, # The temperature used for sampling during response generation. Value ranges from 0 to 1. Temperature controls the degree of randomness in token selection. Lower temperature means less randomness, while higher temperature means more randomness. Valid range: [0.0, 1.0]
    },
    &quot;promptText&quot;: &quot;A String&quot;, # The custom prompt to use.
  },
  &quot;modelParameter&quot;: { # Parameters to be passed to the LLM. If not set, default values will be used. # Parameters passed to the LLM to configure its behavior.
    &quot;maxDecodeSteps&quot;: 42, # The maximum number of tokens to generate.
    &quot;temperature&quot;: 3.14, # The temperature used for sampling. Temperature sampling occurs after both topP and topK have been applied. Valid range: [0.0, 1.0] Low temperature = less random. High temperature = more random.
    &quot;topK&quot;: 42, # If set, the sampling process in each step is limited to the top_k tokens with highest probabilities. Valid range: [1, 40] or 1000+. Small topK = less random. Large topK = more random.
    &quot;topP&quot;: 3.14, # If set, only the tokens comprising the top top_p probability mass are considered. If both top_p and top_k are set, top_p will be used for further refining candidates selected with top_k. Valid range: (0.0, 1.0]. Small topP = less random. Large topP = more random.
  },
  &quot;name&quot;: &quot;A String&quot;, # The unique identifier of the generator. Must be set for the Generators.UpdateGenerator method. Generators.CreateGenerate populates the name automatically. Format: `projects//locations//agents//generators/`.
  &quot;placeholders&quot;: [ # Optional. List of custom placeholders in the prompt text.
    { # Represents a custom placeholder in the prompt text.
      &quot;id&quot;: &quot;A String&quot;, # Unique ID used to map custom placeholder to parameters in fulfillment.
      &quot;name&quot;: &quot;A String&quot;, # Custom placeholder value in the prompt text.
    },
  ],
  &quot;promptText&quot;: { # Text input which can be used for prompt or banned phrases. # Required. Prompt for the LLM model.
    &quot;text&quot;: &quot;A String&quot;, # Required. Text input which can be used for prompt or banned phrases.
  },
}

  languageCode: string, The language to list generators for.
  updateMask: string, The mask to control which fields get updated. If the mask is not present, all fields will be updated.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Generators contain prompt to be sent to the LLM model to generate text. The prompt can contain parameters which will be resolved before calling the model. It can optionally contain banned phrases to ensure the model responses are safe.
  &quot;displayName&quot;: &quot;A String&quot;, # Required. The human-readable name of the generator, unique within the agent. The prompt contains pre-defined parameters such as $conversation, $last-user-utterance, etc. populated by Dialogflow. It can also contain custom placeholders which will be resolved during fulfillment.
  &quot;llmModelSettings&quot;: { # Settings for LLM models. # The LLM model settings.
    &quot;model&quot;: &quot;A String&quot;, # The selected LLM model.
    &quot;parameters&quot;: { # Generative model parameters to control the model behavior. # Generative model parameters.
      &quot;inputTokenLimit&quot;: &quot;A String&quot;, # The input token limit. This setting is currently only supported by playbooks.
      &quot;outputTokenLimit&quot;: &quot;A String&quot;, # The output token limit. This setting is currently only supported by playbooks. Only one of output_token_limit and max_output_tokens is allowed to be set.
      &quot;temperature&quot;: 3.14, # The temperature used for sampling during response generation. Value ranges from 0 to 1. Temperature controls the degree of randomness in token selection. Lower temperature means less randomness, while higher temperature means more randomness. Valid range: [0.0, 1.0]
    },
    &quot;promptText&quot;: &quot;A String&quot;, # The custom prompt to use.
  },
  &quot;modelParameter&quot;: { # Parameters to be passed to the LLM. If not set, default values will be used. # Parameters passed to the LLM to configure its behavior.
    &quot;maxDecodeSteps&quot;: 42, # The maximum number of tokens to generate.
    &quot;temperature&quot;: 3.14, # The temperature used for sampling. Temperature sampling occurs after both topP and topK have been applied. Valid range: [0.0, 1.0] Low temperature = less random. High temperature = more random.
    &quot;topK&quot;: 42, # If set, the sampling process in each step is limited to the top_k tokens with highest probabilities. Valid range: [1, 40] or 1000+. Small topK = less random. Large topK = more random.
    &quot;topP&quot;: 3.14, # If set, only the tokens comprising the top top_p probability mass are considered. If both top_p and top_k are set, top_p will be used for further refining candidates selected with top_k. Valid range: (0.0, 1.0]. Small topP = less random. Large topP = more random.
  },
  &quot;name&quot;: &quot;A String&quot;, # The unique identifier of the generator. Must be set for the Generators.UpdateGenerator method. Generators.CreateGenerate populates the name automatically. Format: `projects//locations//agents//generators/`.
  &quot;placeholders&quot;: [ # Optional. List of custom placeholders in the prompt text.
    { # Represents a custom placeholder in the prompt text.
      &quot;id&quot;: &quot;A String&quot;, # Unique ID used to map custom placeholder to parameters in fulfillment.
      &quot;name&quot;: &quot;A String&quot;, # Custom placeholder value in the prompt text.
    },
  ],
  &quot;promptText&quot;: { # Text input which can be used for prompt or banned phrases. # Required. Prompt for the LLM model.
    &quot;text&quot;: &quot;A String&quot;, # Required. Text input which can be used for prompt or banned phrases.
  },
}</pre>
</div>

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